The aim of the present paper is to enhance the study of solvability
for strong vector equilibrium problems by complementing results about solution
existence with inequalities estimating the distance from the solution set.
These error bounds for \(({\tt SVE})\)  provide useful quantitative information
on the set of solutions, which may be exploited in various contexts of
application. For example, it is well known that error bounds enable to describe
the local geometry of the solution set of a problem through its
tangential (first-order) approximation.
Moreover, error bounds are known to be connected with the metric subregularity
and calmness properties of set-valued mappings (see, for instance, [1]}).
Thus, according to a recognized approach of analysis, error bounds reveal
to be an essential tool for establishing optimality conditions via
penalization techniques. More precisely, the estimates presented
in this paper should be propaedeutic in order for deriving optimality conditions
for MPEC, where equilibrium constraints take the form of strong vector
equilibrium problems (see [2]}).
Furthermore, error bounds turns out to play an important role in
the convergence theory of numerical methods.
